Journal article
Humanization of antibodies using a machine learning approach on large-scale repertoire data
- Abstract:
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Motivation: Monoclonal antibody therapeutics are often produced from non-human sources (typically murine), and can therefore generate immunogenic responses in humans. Humanization procedures aim to produce antibody therapeutics that do not elicit an immune response and are safe for human use, without impacting efficacy. Humanization is normally carried out in a largely trial-and-error experimental process. We have built machine learning classifiers that can discriminate be...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Accepted manuscript, 479.5KB)
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- Publisher copy:
- 10.1093/bioinformatics/btab434
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Authors
Bibliographic Details
- Publisher:
- Oxford University Press Publisher's website
- Journal:
- Bioinformatics Journal website
- Volume:
- 37
- Issue:
- 22
- Pages:
- 4041–4047
- Publication date:
- 2021-06-10
- Acceptance date:
- 2021-06-07
- DOI:
- EISSN:
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1460-2059
- ISSN:
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1367-4803
Item Description
- Language:
- English
- Keywords:
- Pubs id:
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1181328
- Local pid:
- pubs:1181328
- Deposit date:
- 2021-06-10
Terms of use
- Copyright holder:
- Marks et al.
- Copyright date:
- 2021
- Rights statement:
- © The Author(s) 2021. Published by Oxford University Press. All rights reserved.
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from Oxford University Press at: https://doi.org/10.1093/bioinformatics/btab434
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